DISSCUSSION

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2.4 DISSCUSSION

Davis et al. (2012) examine whether a measure of language used throughout an earnings press release is associated with future firm performance and generates a market response. By analyzing a sample of approximately 23,000 quarterly earnings press releases published on PR Newswire between 1998 and 2003, they construct a measure of net optimistic language using an established, textual-analysis software program (DICTION), which counts words characterized as optimistic and negative.

They later find that levels of net optimistic language in earnings press releases are predictive of firm performance in future quarters. They also interpret the evidence to suggest that managers use language in earnings press releases, at least to some extent, to communicate information about expected future firm performance to the market.

These results suggest that market participants consider at least some level of managers’ language to be a credible signal.

Chen et al. (2011) investigate the influence of news coverage on the ERC, which measures the information content of earnings. They collect news articles in the Wall Street Journal from August 1999 through February 2007 to construct measures for news coverage on S&P 500 companies. Combined with data from classical financial databases such as IBES, Compustat and CRSP, they are able to study the effect of news coverage on earnings surprise. Empirical results indicate that news coverage has a significantly negative effect on the ERC; higher news coverage decreases the

information content of earnings and reduces market responses to unexpected earnings.

Mian et al. (2012) examine cross-sectional differences in the stock price response to earnings. The study takes a time-series approach and helps answer the call for more work that incorporates the findings of behavioral finance in capital market research in accounting (Lee 2001). Using a recent proxy of investor sentiment constructed by

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Baker and Wurgler (2006, 2007), they examine how the stock price reaction to earnings news varies with investor sentiment. The results show that the stock price response to good earnings news is higher during periods of high sentiment, whereas stock price reaction to bad earnings news is higher during periods of low sentiment.

This is consistent with the notion that as sentiment increases, investors place increasingly optimistic valuations on the incremental cash flows embedded in earnings announcements.

Davis et al. (2012) investigate whether the proportion of total negative language reported in earnings press releases is associated with the intensity of managers’

strategic reporting incentives. They expect that managers who are more sensitive to the stock price effects of information disclosed face greater incentives to report strategically, and predict that they will report a lower proportion of total negative language in their earnings press releases relative to the MD&A. They find that managers of high-growth firms and firms that exactly meet or just beat earnings benchmarks in the current quarter report a lower proportion of total negative language in their earnings press releases. They also find evidence consistent with managers who habitually meet or just beat analysts’ earnings forecasts reporting a lower proportion of total negative language in their earnings press releases.

Tama-Sweet (2014) investigates the association between changes in the

optimistic tone of earnings announcements and CEOs' equity sales. Using a sample of approximately 20,000 firm-quarters from 1998 to 2007, he finds a positive relation between changes in earnings announcement tone and CEO equity sales. The positive relation is mitigated by SOX and by litigation risk. Consistent with the literature, he also finds a positive relation between changes in optimistic tone in earnings

announcements and abnormal returns.

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This study implements the ideas of prior works and adds different sources of information and method to conduct content analysis. Some of the variables are chosen and some are not because of different databases used and availability of data. The summary of related works is in the following table.

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The following table discusses the literature review mentioned in section 2.4, including lists of author, hypothesis, model, variable definition and adopted variable in this study.

Table 2-1. Summary of Related Research

Author Hypothesis Model Adopted Variable

Beyond the earnings announcement, scaled by stock price measured at the beginning of the current quarter. BEAT is a dummy variable, to be 1 if announced earnings for the current quarter met or exceeded analysts' expectations and 0 otherwise. LOSS is a dummy variable, to be 1 if earnings are negative and 0 otherwise. DET_FS is a dummy variable, define BS_D and SCF_D to be 1 if these word counts are greater than two for balance sheet -related words and greater than one for statement of cash flow -related words, respectively. If the sum of BS_D and SCF_D is greater than 0 and include it in our analyses as a control for the presence of detailed financial statements. DIV_INC is a

CAR,

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Author Hypothesis Model Adopted Variable

dummy variable, to be 1 if the dividend change is positive. NONREC_POS is a dummy variable, to be 1 if the net effect of these components on current period earnings is positive and zero otherwise. NONREC_NEG is a dummy variable, to be 1 if the net effect of these components on current period earnings is negative and zero otherwise.

PM is profit margin. AT is asset turnover. DA is total liabilities scaled by total assets (both measured at the end of the current quarter). BM is book-to-market ratio as the book value of equity scaled by the market value of equity (both measured at the end of the current quarter). NETOPT is the difference between the percentage of optimistic words and the percentage of pessimistic words. ID is an indicator variable, taking the value 1 if the press release represented in observation i is for a firm in the jth two-digit SIC industry and 0 otherwise. YEAR is an indicator variable, taking the value 1 if the earnings press release represented in observation i was released in year k and 0 otherwise.

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Author Hypothesis Model Adopted Variable

Giving context

relative to an earnings announcement day t. UE is the unexpected earnings computed based on the difference between the realized earnings and analysts' forecasts, divided by the stock price of firm i at day t. DUE is a dummy variable, where is 1 if UE is positive and 0 if UE is negative. FFalpha is the estimated intercept in the Fama–French three-factor model used to compute abnormal returns. SIZE is firms' market value at time t. BM is book-to-market ratio at time t. STurnover is share turnover rate during the reporting quarter associated with time t. NewsFrequency is Number of news articles that have mentioned firm i during the trading day window [−20, −1] relative to the earnings announcement date t.

CAR,

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Author Hypothesis Model Adopted Variable

Investor periods of high sentiment, whereas the ERC of bad news is higher during periods

Earnings is the primary earnings per share of firm i for quarter q. RET is the cumulative abnormal return for firm i during the earnings announcement event window from day -1 to +-1 centered on the earnings announcement date in calendar month t. Up is a dummy variable, equals 1 if the unexpected earnings is positive, and 0 otherwise. Earnings is the primary earnings per share of firm i for quarter q. P is the price per share at the end of quarter q. Down is a dummy variable, equals 1 if the unexpected earnings is negative, and 0 otherwise. Sent is the sentiment index developed by Baker and Wurgler (2006, 2007), which is available on a monthly basis. NonlUp is the square of UEUp.

NonlDown is the square of multiplied by -1. MktPE is market price-to-earnings ratio.

RET, Down, Up, MktPE

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Author Hypothesis Model Adopted Variable

Managers’ Use press release and MD&A is negatively related to market returns around

CAR is the cumulative abnormal return relative to the firm’s size-decile portfolio over the three-day window centered on the earnings press release date. SURP is the difference between actual earnings and the most recent consensus analyst earnings forecast made prior to the earnings announcement, scaled by stock price measured at the beginning of the current quarter. BEAT is a dummy variable, to be 1 if announced earnings for the current quarter met or exceeded analysts' expectations and 0 otherwise.

LOSS is a dummy variable, to be 1 if earnings are negative and 0 otherwise.

UNEXP_PESS_PR is unexpected pessimistic language in the press release from a random walk model. IND and YEAR is year and industry.

CAR, SURP, BEAT, LOSS,

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Author Hypothesis Model Adopted Variable

Changes in changes in the optimistic tone until the day of a CEO equity sale. OPTIMISM_PR use DICTION_PC as dependent variable in tests. SURP is the difference between actual earnings and the most recent consensus analyst earnings forecast made prior to the earnings announcement, scaled by stock price measured at the beginning of the current quarter. BEAT is a dummy variable, to be 1 if announced earnings for the current quarter met or exceeded analysts' expectations and 0 otherwise. LOSS is a dummy variable, to be 1 if earnings are negative and 0 otherwise. QTR, YEAR, and INDSTRY are indicators for quarter, year, and industry.

Table source: this research

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